Bottom Line:
After evaluation, most of the predicted modules are found to be biologically significant and functionally homogeneous.Six pathogenicity-related modules were discovered and analyzed, including novel modules.Our study also provides a strategy for applying modularity analysis to any sequenced organism.

Background: With the development of experimental techniques and bioinformatics, the quantity of data available from protein-protein interactions (PPIs) is increasing exponentially. Functional modules can be identified from protein interaction networks. It follows that the investigation of functional modules will generate a better understanding of cellular organization, processes, and functions. However, experimental PPI data are still limited, and no modularity analysis of PPIs in pathogens has been published to date.

Results: In this study, we predict and analyze the functional modules of E. coli O157:H7 systemically by integrating several bioinformatics methods. After evaluation, most of the predicted modules are found to be biologically significant and functionally homogeneous. Six pathogenicity-related modules were discovered and analyzed, including novel modules. These modules provided new information on the pathogenicity of O157:H7. The modularity of cellular function and cooperativity between modules are also discussed. Moreover, modularity analysis of O157:H7 can provide possible candidates for biological pathway extension and clues for discovering new pathways of cross-talk.

Conclusions: This article provides the first modularity analysis of a pathogen and sheds new light on the study of pathogens and cellular processes. Our study also provides a strategy for applying modularity analysis to any sequenced organism.

Mentions:
Figure 7 consists of five small modules related to cell division in O157. In the green module, FtsZ is a GTPase that forms a ring-like structure known as the Z-ring at the midcell boundary [61,62]. There are some similarities between FtsZ and tubulin, so it is not surprising that the Z-ring is a highly dynamic structure. ZipA is a stabilizing factor of the Z-ring [63], while proteins in the yellow module are destabilizing factors of the Z-ring [64]. SopA and SopB, in the red module, are related to the partitioning of the plasmid during cell division. After BLAST, we found that two of the three hypothetical proteins in the red module were highly similar to ParA and ParB, which are also related to partitioning of the plasmid [65]. MurF, MurC, and MurE, in the blue module, are associated with cell envelope biosynthesis [66]. The Fts proteins in the purple module assemble on the Z-ring in order, though their functions are still not clear. The other proteins in the purple module are related to cell wall biosynthesis [67].

Mentions:
Figure 7 consists of five small modules related to cell division in O157. In the green module, FtsZ is a GTPase that forms a ring-like structure known as the Z-ring at the midcell boundary [61,62]. There are some similarities between FtsZ and tubulin, so it is not surprising that the Z-ring is a highly dynamic structure. ZipA is a stabilizing factor of the Z-ring [63], while proteins in the yellow module are destabilizing factors of the Z-ring [64]. SopA and SopB, in the red module, are related to the partitioning of the plasmid during cell division. After BLAST, we found that two of the three hypothetical proteins in the red module were highly similar to ParA and ParB, which are also related to partitioning of the plasmid [65]. MurF, MurC, and MurE, in the blue module, are associated with cell envelope biosynthesis [66]. The Fts proteins in the purple module assemble on the Z-ring in order, though their functions are still not clear. The other proteins in the purple module are related to cell wall biosynthesis [67].

Bottom Line:
After evaluation, most of the predicted modules are found to be biologically significant and functionally homogeneous.Six pathogenicity-related modules were discovered and analyzed, including novel modules.Our study also provides a strategy for applying modularity analysis to any sequenced organism.

Background: With the development of experimental techniques and bioinformatics, the quantity of data available from protein-protein interactions (PPIs) is increasing exponentially. Functional modules can be identified from protein interaction networks. It follows that the investigation of functional modules will generate a better understanding of cellular organization, processes, and functions. However, experimental PPI data are still limited, and no modularity analysis of PPIs in pathogens has been published to date.

Results: In this study, we predict and analyze the functional modules of E. coli O157:H7 systemically by integrating several bioinformatics methods. After evaluation, most of the predicted modules are found to be biologically significant and functionally homogeneous. Six pathogenicity-related modules were discovered and analyzed, including novel modules. These modules provided new information on the pathogenicity of O157:H7. The modularity of cellular function and cooperativity between modules are also discussed. Moreover, modularity analysis of O157:H7 can provide possible candidates for biological pathway extension and clues for discovering new pathways of cross-talk.

Conclusions: This article provides the first modularity analysis of a pathogen and sheds new light on the study of pathogens and cellular processes. Our study also provides a strategy for applying modularity analysis to any sequenced organism.